The retail landscape changed since the onset of COVID in ways most industry executives are still trying to wrap their heads around. And nowhere will these changes impact the retail industry in such a significant fashion than in the areas of customer engagement and consumer experience. Customers have always wanted the ‘Royal Treatment’ but the dynamics of how to deliver an authentic, bespoke experience at scale in today’s ultra-competitive, always on, and dynamic retail environment is not what it used to be only a few years ago. Consumer expectations are different, and so are the tools at the disposal of retailers.
That a sector undergoes change, of course, is nothing new. Since the advent of the consumerization of the internet in the late 1990s, the pace of change in retail has always been on a gradually accelerating swoop. Looking back, nearly every facet of the business has been upended in such a remarkable fashion in the last quarter of a century to such an extent that it is almost an entirely new business for the older retail execs in their 60s and 70s who have been in the industry their entire professional lives; for them, it must be both amazing and somewhat bizarre to compare the retail landscape of today with the one they entered 30 or 40 years ago. In fact, a retail marketing executive from 1992 would probably have far more in common with his counterpart from 1932 than with his equivalent in 2022.
And it’s not just the growth of the internet and e-commerce. Take for example brands that are now direct to consumer (DTC) players – a shift in the playing field so profound that it has transformed them into “frenemies” of the retailers they so-often wholly depended on in the past. Yes the technology has been a catalyst for much of the innovation across the sector, but a changing culture and demographics continue to play equally decisive roles.
But although all this change that has swept across the sector in the last few decades is striking, it pales in comparison to the next wave of change that has been unleashed ever since the pandemic upended daily life across the planet. Make no mistake about it: the retail industry is entering a new phase of hyper-change, or as some have described it, ‘exponential change.’
Business models have changed in profound ways that have completely upended how supply chains are managed and how sourcing and buying takes place. Furthermore, logistics and distribution have become infinitely more complex while merchandising, marketing, and consumer engagement have become powered by data, artificial intelligence (AI), and, importantly, psychology.
Take, for example, the concept of “comparison shopping.” In the so-called “old school” days of retailing (i.e. anytime pre-1990s), it generally went like this: customers showed up at a store, saw what was being offered, and made their purchases accordingly. With few exceptions, there wasn’t much comparison shopping. Nearly everything on the showroom floor was unique to that retailer – white label products or brands created by suppliers with specific retailers in mind.
In fact, if there was much price comparison done at all, it amounted to a highly time-intensive, inefficient process that required consumers to actually “hoof it” (i.e. visit multiple store locations), thumb through voluminous catalog mailers, or peruse Sunday newspaper inserts.
Of course, all that has changed; nowadays, consumers prefer to shop from the comfort of their homes or smartphones and do so with an impressive arsenal of comparison-shopping tools. Armed with a near endless stream of easily accessible consumer product guides, YouTube unboxing videos, and Reddit threads, retail consumers in 2022 are contending with the exact opposite problem that confronted their parents and grandparents: too much information.
Retail is Entering a New Period of Exponential Change
All these changes that have taken place over the past several decades, although they have been swift and dramatic, might be best characterized simply as geometric change. From, say, the mid-1990s to 2018 or so, changes across the retail landscape came at a rapid, albeit, predictable and somewhat manageable pace. Yet what economists and retail observers are beginning to sense is that the pace of change already underfoot in the sector over the past few years suggests that the retail sector is no longer in the throes of geometric change; it is clearly in the early phases of exponential change. And although COVID-19 was the likely catalyst that turned the retail landscape upside down, the real change agent is the emergence of sophisticated AI that has now reached a point of maturation such that it can be effectively deployed at scale across the entire sector.Before we get too far ahead of ourselves, let’s take a trip in “Doc” Brown’s DeLorean time machine to the days of high school algebra class and remind ourselves of the difference between geometric and exponential growth, with the latter referring to a growth pattern where every x is multiplied by the same fixed positive number, resulting in an upward trajectory that curves over time. Exponential growth, by contrast, refers to a growth pattern in which a fixed number is raised to the power of x. From a practical eyes-on-the-ground perspective, exponential growth might seem not so different from geometric growth in the early stages of a sequence, but the power of exponentiation soon separates these two models for projecting change. Take, for example, the first 90 days of the COVID-19 lockdowns in which e-commerce in the US grew more than in the previous ten years. That’s an example of an exponential change in shopping behavior. Now, admittedly, this is a somewhat weighty topic for an essay dealing with retail customer experience, but it is, nevertheless, an important one because it is in 2022 that the exponentiality of the vectors of change making its way across the sector will begin to become apparent to the average observer. And nowhere will this change in retail become more apparent than in the realm of customer experience.
The Pillars of Customer Experience: AI-enabled Personalization & Authenticity
For the proprietor of a boutique clothing shop in a small town, a high degree of customer personalization is likely feasible without employing all the tools of the trade available in 2022. But for everyone else – any retail operation with a modicum of scale – true personalization will only be made possible by employing sophisticated data science and AI-powered algorithms that can not only track customer shopping habits and preferences but, more importantly, can predict likes, needs, and desires on a granular level. It’s no longer about making sweeping assumptions about consumer demand (e.g. “shoppers will love that the herringbone pattern is back in style this season.”) Rather, it’s a question of being able to collect, parse, and analyze a near-endless stream of data to make billions of reliable consumer-specific predictions at scale (e.g. “Priscila from Peoria will need a new winter jacket in the next four weeks and she will likely be drawn to items that offer a herringbone pattern option in $160-$190 price range.”) The same goes for language. And how a retailer communicates with Priscila from Peoria about a new herringbone pattern jacket will necessarily be different than how it communicates with her sister Chandra in Chicago. The non-verbal and visual cues, the emotion conveyed in the marketing pitch, the syntax of sentence structure, the vocabulary – all of these small details can no longer be left to chance. Each consumer’s unique and always-evolving purchasing patterns are knowable, but only in recent years have technology and data science been able to capture and effectively leverage these inputs into an actionable consumer engagement strategy that provides a sense of a personalized experience that doesn’t compromise authenticity. Consumers are constantly leaving breadcrumbs after every online interaction or experience. And it’s up to retailers to follow these tiny morsels of data, piece them together, make educated assumptions to fill in the blanks, and generate near-perfect predictive algorithms for each customer. Today’s highly demanding customers are not like the customers of the 1990s nor even like those of the 2010s. The consumer of 2022 expects to be treated like royalty. Like sitting monarchs, today’s consumers are impetuous and impatient; they grow quickly intolerant of brands that don’t seem to understand what they like or how they like to be presented with choices. Some prefer to read in Avenir, others in Arial Nova. Oftentimes, mostly on a subconscious level, they have a way in which they prefer to be spoken to and presented with information and choices. Bottomline, language matters. Context matters. Visuals matter. And retailers need to get it right. If they don’t, consumers will move on, a fact borne out by a recent McKinsey report which concluded that 75% of U.S. consumers have changed their shopping behavior, including product brands and retailers, since the onset of COVID-19. Today’s average consumer wants the royal treatment with all the bespoke trappings befit of a monarch; yet for retailers, the only way of delivering this degree of customization is through the power of next generation AI. Welcome to 2022, everyone.
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